{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Hamiltonian and Gate Characterization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook gives examples to demonstrate how to use the ``characterization.hamiltonian`` and ``characterization.gates`` modules in Qiskit Ignis. For a theory background see the [Ignis Community Notebooks]( https://github.com/Qiskit/qiskit-community-tutorials/tree/master/ignis)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import qiskit\n",
    "from qiskit.providers.aer.noise.errors.standard_errors import coherent_unitary_error\n",
    "from qiskit.providers.aer.noise import NoiseModel\n",
    "\n",
    "from qiskit.ignis.characterization.hamiltonian import ZZFitter, zz_circuits\n",
    "\n",
    "from qiskit.ignis.characterization.gates import (AmpCalFitter, ampcal_1Q_circuits, \n",
    "                                                 AngleCalFitter, anglecal_1Q_circuits, \n",
    "                                                 AmpCalCXFitter, ampcal_cx_circuits, \n",
    "                                                 AngleCalCXFitter, anglecal_cx_circuits)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Measuring ZZ\n",
    "\n",
    "The ``characterization.hamiltonian.zz_circuits`` module builds the circuits to perform an experiment to measure ZZ between a pair of qubits.  Here, ZZ is defined as the energy shift on the $|11\\rangle$ state:\n",
    "\n",
    "$$H=\\omega_0 (1-\\sigma_{Z,0})/2 +\\omega_1 (1-\\sigma_{Z,1})/2 + \\xi |11\\rangle\\langle 11|$$\n",
    "\n",
    "The experiment to measure $\\xi$ is to perform a Ramsey experiment on Q0 (H-t-H) and repeat the Ramsey experiment with Q1 in the excited state. The difference in frequency between these experiments is the rate $\\xi$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-18T15:34:52.275440Z",
     "start_time": "2018-12-18T15:32:05.667514Z"
    }
   },
   "outputs": [],
   "source": [
    "# ZZ rates are typically ~ 100kHz so we want Ramsey oscillations around 1MHz\n",
    "# 12 numbers ranging from 10 to 1000, logarithmically spaced\n",
    "# extra point at 1500\n",
    "num_of_gates = np.arange(0,150,5)\n",
    "gate_time = 0.1\n",
    "\n",
    "# Select the qubits whose ZZ will be measured\n",
    "qubits = [0]\n",
    "spectators = [1]\n",
    "\n",
    "# Generate experiments\n",
    "circs, xdata, osc_freq = zz_circuits(num_of_gates, gate_time, qubits, spectators, nosc=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One of the features of the fitters is that we can split the circuits into multiple jobs and then give the results to the fitter as a list. This is demonstrated below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running the first 20 circuits\n",
      "Running the rest of the circuits\n"
     ]
    }
   ],
   "source": [
    "# Set the simulator with ZZ\n",
    "zz_unitary = np.eye(4,dtype=complex)\n",
    "zz_unitary[3,3] = np.exp(1j*2*np.pi*0.02*gate_time)\n",
    "error = coherent_unitary_error(zz_unitary)\n",
    "noise_model = NoiseModel()\n",
    "noise_model.add_nonlocal_quantum_error(error, 'id', [0], [0,1])\n",
    "\n",
    "# Run the simulator\n",
    "backend = qiskit.Aer.get_backend('qasm_simulator')\n",
    "shots = 500\n",
    "# For demonstration purposes split the execution into two jobs\n",
    "print(\"Running the first 20 circuits\")\n",
    "backend_result1 = qiskit.execute(circs[0:20], backend,\n",
    "                                shots=shots, noise_model=noise_model).result()\n",
    "print(\"Running the rest of the circuits\")\n",
    "backend_result2 = qiskit.execute(circs[20:], backend,\n",
    "                                shots=shots, noise_model=noise_model).result()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": [
     "nbsphinx-thumbnail"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ZZ Rate: 20.602746 kHz\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "# Fit the data to an oscillation\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "initial_a = 1\n",
    "initial_c = 0\n",
    "initial_f = osc_freq \n",
    "initial_phi = -np.pi/20\n",
    "\n",
    "# Instantiate the fitter\n",
    "# pass the 2 results in as a list of results\n",
    "fit = ZZFitter([backend_result1, backend_result2], xdata, qubits, spectators,\n",
    "                   fit_p0=[initial_a, initial_f, initial_phi, initial_c],\n",
    "                   fit_bounds=([-0.5, 0, -np.pi, -0.5],\n",
    "                               [1.5, 2*osc_freq, np.pi, 1.5]))\n",
    "\n",
    "fit.plot_ZZ(0, ax=plt.gca())\n",
    "    \n",
    "print(\"ZZ Rate: %f kHz\"%(fit.ZZ_rate()[0]*1e3))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Amplitude Error Characterization for Single Qubit Gates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Measure the amplitude error in the single qubit gates. Here this measures the error in the $\\pi/2$ pulse. Note that we can run multiple amplitude calibrations in parallel. Here we measure on qubits 2 and 4. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "qubits = [4,2]\n",
    "circs, xdata = ampcal_1Q_circuits(10, qubits)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This shows the sequence of the calibration, which is a repeated application of Y90 (U2[0,0]). Note that the measurements are mapped to a minimal number of classical registers in order of the qubit list."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                                               »\n",
      "q1_0: |0>──────────────────────────────────────────────────────────────────────»\n",
      "                                                                               »\n",
      "q1_1: |0>──────────────────────────────────────────────────────────────────────»\n",
      "         ┌─────────┐ ░ ┌─────────┐ ░ ┌─────────┐ ░ ┌─────────┐ ░ ┌─────────┐   »\n",
      "q1_2: |0>┤ U2(0,0) ├─░─┤ U2(0,0) ├─░─┤ U2(0,0) ├─░─┤ U2(0,0) ├─░─┤ U2(0,0) ├───»\n",
      "         └─────────┘ ░ └─────────┘ ░ └─────────┘ ░ └─────────┘ ░ └─────────┘   »\n",
      "q1_3: |0>──────────────────────────────────────────────────────────────────────»\n",
      "         ┌─────────┐ ░ ┌─────────┐ ░ ┌─────────┐ ░ ┌─────────┐ ░ ┌─────────┐┌─┐»\n",
      "q1_4: |0>┤ U2(0,0) ├─░─┤ U2(0,0) ├─░─┤ U2(0,0) ├─░─┤ U2(0,0) ├─░─┤ U2(0,0) ├┤M├»\n",
      "         └─────────┘ ░ └─────────┘ ░ └─────────┘ ░ └─────────┘ ░ └─────────┘└╥┘»\n",
      " c1_0: 0 ════════════════════════════════════════════════════════════════════╩═»\n",
      "                                                                               »\n",
      " c1_1: 0 ══════════════════════════════════════════════════════════════════════»\n",
      "                                                                               »\n",
      "«         \n",
      "«q1_0: ───\n",
      "«         \n",
      "«q1_1: ───\n",
      "«      ┌─┐\n",
      "«q1_2: ┤M├\n",
      "«      └╥┘\n",
      "«q1_3: ─╫─\n",
      "«       ║ \n",
      "«q1_4: ─╫─\n",
      "«       ║ \n",
      "«c1_0: ═╬═\n",
      "«       ║ \n",
      "«c1_1: ═╩═\n",
      "«         \n"
     ]
    }
   ],
   "source": [
    "print(circs[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set the simulator \n",
    "# Add a rotation error\n",
    "err_unitary = np.zeros([2,2],dtype=complex)\n",
    "angle_err = 0.1\n",
    "for i in range(2):\n",
    "    err_unitary[i,i] = np.cos(angle_err)\n",
    "    err_unitary[i,(i+1) % 2] = np.sin(angle_err)\n",
    "err_unitary[0,1] *= -1.0\n",
    "\n",
    "error = coherent_unitary_error(err_unitary)\n",
    "noise_model = NoiseModel()\n",
    "noise_model.add_all_qubit_quantum_error(error, 'u2')\n",
    "\n",
    "# Run the simulator\n",
    "backend = qiskit.Aer.get_backend('qasm_simulator')\n",
    "shots = 500\n",
    "backend_result1 = qiskit.execute(circs, backend,\n",
    "                                shots=shots, noise_model=noise_model).result()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rotation Error on U2: 0.100412 rads\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "# Fit the data to an oscillation\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "initial_theta = 0.02\n",
    "initial_c = 0.5\n",
    "initial_phi = 0.1\n",
    "\n",
    "\n",
    "fit = AmpCalFitter(backend_result1, xdata, qubits,\n",
    "                   fit_p0=[initial_theta, initial_c],\n",
    "                   fit_bounds=([-np.pi, -1],\n",
    "                               [np.pi, 1]))\n",
    "\n",
    "# plot the result for the number 1 indexed qubit.\n",
    "# In this case that refers to Q2 since we passed in as [4, 2])\n",
    "fit.plot(1, ax=plt.gca())\n",
    "    \n",
    "print(\"Rotation Error on U2: %f rads\"%(fit.angle_err()[0]))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Angle Error Characterization for Single Qubit Gates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Measure the angle between the X and Y gates:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "qubits = [0,1]\n",
    "circs, xdata = anglecal_1Q_circuits(10, qubits, angleerr=0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The gate sequence for measuring the angle error:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         ┌─────────┐┌──────────┐ ░ ┌────────────────┐ ░ ┌────────────────┐»\n",
      "q2_0: |0>┤ U2(0,0) ├┤ U1(-0.2) ├─░─┤ U2(-pi/2,pi/2) ├─░─┤ U2(-pi/2,pi/2) ├»\n",
      "         ├─────────┤├──────────┤ ░ ├────────────────┤ ░ ├────────────────┤»\n",
      "q2_1: |0>┤ U2(0,0) ├┤ U1(-0.2) ├─░─┤ U2(-pi/2,pi/2) ├─░─┤ U2(-pi/2,pi/2) ├»\n",
      "         └─────────┘└──────────┘ ░ └────────────────┘ ░ └────────────────┘»\n",
      " c2_0: 0 ═════════════════════════════════════════════════════════════════»\n",
      "                                                                          »\n",
      " c2_1: 0 ═════════════════════════════════════════════════════════════════»\n",
      "                                                                          »\n",
      "«      ┌─────────┐ ░ ┌─────────┐ ░ ┌─────────┐┌──────────┐ ░ ┌────────────────┐»\n",
      "«q2_0: ┤ U1(0.2) ├─░─┤ U2(0,0) ├─░─┤ U2(0,0) ├┤ U1(-0.2) ├─░─┤ U2(-pi/2,pi/2) ├»\n",
      "«      ├─────────┤ ░ ├─────────┤ ░ ├─────────┤├──────────┤ ░ ├────────────────┤»\n",
      "«q2_1: ┤ U1(0.2) ├─░─┤ U2(0,0) ├─░─┤ U2(0,0) ├┤ U1(-0.2) ├─░─┤ U2(-pi/2,pi/2) ├»\n",
      "«      └─────────┘ ░ └─────────┘ ░ └─────────┘└──────────┘ ░ └────────────────┘»\n",
      "«c2_0: ════════════════════════════════════════════════════════════════════════»\n",
      "«                                                                              »\n",
      "«c2_1: ════════════════════════════════════════════════════════════════════════»\n",
      "«                                                                              »\n",
      "«       ░ ┌────────────────┐┌─────────┐ ░ ┌─────────┐ ░ ┌─────────┐┌──────────┐»\n",
      "«q2_0: ─░─┤ U2(-pi/2,pi/2) ├┤ U1(0.2) ├─░─┤ U2(0,0) ├─░─┤ U2(0,0) ├┤ U1(-0.1) ├»\n",
      "«       ░ ├────────────────┤├─────────┤ ░ ├─────────┤ ░ ├─────────┤├──────────┤»\n",
      "«q2_1: ─░─┤ U2(-pi/2,pi/2) ├┤ U1(0.2) ├─░─┤ U2(0,0) ├─░─┤ U2(0,0) ├┤ U1(-0.1) ├»\n",
      "«       ░ └────────────────┘└─────────┘ ░ └─────────┘ ░ └─────────┘└──────────┘»\n",
      "«c2_0: ════════════════════════════════════════════════════════════════════════»\n",
      "«                                                                              »\n",
      "«c2_1: ════════════════════════════════════════════════════════════════════════»\n",
      "«                                                                              »\n",
      "«      ┌────────────────┐┌─┐   \n",
      "«q2_0: ┤ U2(-pi/2,pi/2) ├┤M├───\n",
      "«      ├────────────────┤└╥┘┌─┐\n",
      "«q2_1: ┤ U2(-pi/2,pi/2) ├─╫─┤M├\n",
      "«      └────────────────┘ ║ └╥┘\n",
      "«c2_0: ═══════════════════╩══╬═\n",
      "«                            ║ \n",
      "«c2_1: ══════════════════════╩═\n",
      "«                              \n"
     ]
    }
   ],
   "source": [
    "#The U1 gates are added errors to test the procedure\n",
    "print(circs[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set the simulator \n",
    "# Run the simulator\n",
    "backend = qiskit.Aer.get_backend('qasm_simulator')\n",
    "shots = 1000\n",
    "backend_result1 = qiskit.execute(circs, backend,\n",
    "                                shots=shots).result()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Angle error between X and Y: 0.096159 rads\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "# Fit the data to an oscillation\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "initial_theta = 0.02\n",
    "initial_c = 0.5\n",
    "initial_phi = 0.01\n",
    "\n",
    "\n",
    "fit = AngleCalFitter(backend_result1, xdata, qubits,\n",
    "                   fit_p0=[initial_theta, initial_c],\n",
    "                   fit_bounds=([-np.pi, -1],\n",
    "                               [np.pi, 1]))\n",
    "\n",
    "fit.plot(0, ax=plt.gca())\n",
    "    \n",
    "print(\"Angle error between X and Y: %f rads\"%(fit.angle_err()[0]))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Amplitude Error Characterization for CX Gates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This looks for a rotation error in the CX gate, i.e. if the gate is actually $CR_x(\\pi/2+\\delta)$ measure $\\delta$. This is very similar to the single qubit amplitude error calibration except we need to specify a control qubit (which is set to be in state $|1\\rangle$) and the rotation is $\\pi$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We can specify more than one CX gate to calibrate in parallel\n",
    "# but these lists must be the same length and not contain\n",
    "# any duplicate elements\n",
    "qubits = [0,2]\n",
    "controls = [1,3]\n",
    "circs, xdata = ampcal_cx_circuits(15, qubits, controls)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The gate sequence to calibrate the amplitude of the CX gate on Q0-Q1 and Q2-Q3 in parallel:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         ┌────────────────┐ ░ ┌───┐ ░ ┌───┐┌─┐   \n",
      "q3_0: |0>┤ U2(-pi/2,pi/2) ├─░─┤ X ├─░─┤ X ├┤M├───\n",
      "         └─────┬───┬──────┘ ░ └─┬─┘ ░ └─┬─┘└╥┘   \n",
      "q3_1: |0>──────┤ X ├────────░───■───░───■───╫────\n",
      "         ┌─────┴───┴──────┐ ░ ┌───┐ ░ ┌───┐ ║ ┌─┐\n",
      "q3_2: |0>┤ U2(-pi/2,pi/2) ├─░─┤ X ├─░─┤ X ├─╫─┤M├\n",
      "         └─────┬───┬──────┘ ░ └─┬─┘ ░ └─┬─┘ ║ └╥┘\n",
      "q3_3: |0>──────┤ X ├────────░───■───░───■───╫──╫─\n",
      "               └───┘        ░       ░       ║  ║ \n",
      " c3_0: 0 ═══════════════════════════════════╩══╬═\n",
      "                                               ║ \n",
      " c3_1: 0 ══════════════════════════════════════╩═\n",
      "                                                 \n"
     ]
    }
   ],
   "source": [
    "print(circs[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set the simulator \n",
    "# Add a rotation error on CX\n",
    "# only if the control is in the excited state\n",
    "err_unitary = np.eye(4,dtype=complex)\n",
    "angle_err = 0.15\n",
    "for i in range(2):\n",
    "    err_unitary[2+i,2+i] = np.cos(angle_err)\n",
    "    err_unitary[2+i,2+(i+1) % 2] = -1j*np.sin(angle_err)\n",
    "\n",
    "error = coherent_unitary_error(err_unitary)\n",
    "noise_model = NoiseModel()\n",
    "noise_model.add_nonlocal_quantum_error(error, 'cx', [1,0], [0,1])\n",
    "\n",
    "# Run the simulator\n",
    "backend = qiskit.Aer.get_backend('qasm_simulator')\n",
    "shots = 1500\n",
    "backend_result1 = qiskit.execute(circs, backend,\n",
    "                                shots=shots, noise_model=noise_model).result()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rotation Error on CX: 0.149493 rads\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "# Fit the data to an oscillation\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "initial_theta = 0.02\n",
    "initial_c = 0.5\n",
    "initial_phi = 0.01\n",
    "\n",
    "\n",
    "fit = AmpCalCXFitter(backend_result1, xdata, qubits,\n",
    "                   fit_p0=[initial_theta, initial_c],\n",
    "                   fit_bounds=([-np.pi, -1],\n",
    "                               [np.pi, 1]))\n",
    "\n",
    "fit.plot(0, ax=plt.gca())\n",
    "    \n",
    "print(\"Rotation Error on CX: %f rads\"%(fit.angle_err()[0]))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Angle Error Characterization for CX Gates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Measure the angle error $\\theta$ in the CX gate, i.e. $CR_{\\cos(\\theta)X+\\sin(\\theta)Y}(\\pi/2)$ with respect to the angle of the single qubit gates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "qubits = [0,2]\n",
    "controls = [1,3]\n",
    "circs, xdata = anglecal_cx_circuits(15, qubits, controls, angleerr=0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The gate sequence to calibrate the CX angle for Q0-Q1 and Q3-Q4 in parallel:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         ┌─────────┐┌──────────┐ ░ ┌───┐┌─────────┐┌───┐┌──────────┐ ░ ┌───┐»\n",
      "q4_0: |0>┤ U2(0,0) ├┤ U1(-0.1) ├─░─┤ X ├┤ U1(0.1) ├┤ Y ├┤ U1(-0.1) ├─░─┤ X ├»\n",
      "         └──┬───┬──┘└──────────┘ ░ └─┬─┘└─────────┘└───┘└──────────┘ ░ └─┬─┘»\n",
      "q4_1: |0>───┤ X ├────────────────░───■───────────────────────────────░───■──»\n",
      "         ┌──┴───┴──┐┌──────────┐ ░ ┌───┐┌─────────┐┌───┐┌──────────┐ ░ ┌───┐»\n",
      "q4_2: |0>┤ U2(0,0) ├┤ U1(-0.1) ├─░─┤ X ├┤ U1(0.1) ├┤ Y ├┤ U1(-0.1) ├─░─┤ X ├»\n",
      "         └──┬───┬──┘└──────────┘ ░ └─┬─┘└─────────┘└───┘└──────────┘ ░ └─┬─┘»\n",
      "q4_3: |0>───┤ X ├────────────────░───■───────────────────────────────░───■──»\n",
      "            └───┘                ░                                   ░      »\n",
      " c4_0: 0 ═══════════════════════════════════════════════════════════════════»\n",
      "                                                                            »\n",
      " c4_1: 0 ═══════════════════════════════════════════════════════════════════»\n",
      "                                                                            »\n",
      "«      ┌─────────┐┌───┐┌────────────────┐┌─┐   \n",
      "«q4_0: ┤ U1(0.1) ├┤ Y ├┤ U2(-pi/2,pi/2) ├┤M├───\n",
      "«      └─────────┘└───┘└────────────────┘└╥┘   \n",
      "«q4_1: ───────────────────────────────────╫────\n",
      "«      ┌─────────┐┌───┐┌────────────────┐ ║ ┌─┐\n",
      "«q4_2: ┤ U1(0.1) ├┤ Y ├┤ U2(-pi/2,pi/2) ├─╫─┤M├\n",
      "«      └─────────┘└───┘└────────────────┘ ║ └╥┘\n",
      "«q4_3: ───────────────────────────────────╫──╫─\n",
      "«                                         ║  ║ \n",
      "«c4_0: ═══════════════════════════════════╩══╬═\n",
      "«                                            ║ \n",
      "«c4_1: ══════════════════════════════════════╩═\n",
      "«                                              \n"
     ]
    }
   ],
   "source": [
    "print(circs[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set the simulator \n",
    "# Run the simulator\n",
    "backend = qiskit.Aer.get_backend('qasm_simulator')\n",
    "shots = 1000\n",
    "backend_result1 = qiskit.execute(circs, backend,\n",
    "                                shots=shots).result()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rotation Error on CX: 0.099402 rads\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "# Fit the data to an oscillation\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "initial_theta = 0.02\n",
    "initial_c = 0.5\n",
    "initial_phi = 0.01\n",
    "\n",
    "\n",
    "fit = AngleCalCXFitter(backend_result1, xdata, qubits,\n",
    "                   fit_p0=[initial_theta, initial_c],\n",
    "                   fit_bounds=([-np.pi, -1],\n",
    "                               [np.pi, 1]))\n",
    "\n",
    "fit.plot(0, ax=plt.gca())\n",
    "    \n",
    "print(\"Rotation Error on CX: %f rads\"%(fit.angle_err()[0]))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T01:30:24.349385Z",
     "start_time": "2019-08-22T01:30:24.340068Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<h3>Version Information</h3><table><tr><th>Qiskit Software</th><th>Version</th></tr><tr><td>Qiskit</td><td>None</td></tr><tr><td>Terra</td><td>0.9.0</td></tr><tr><td>Aer</td><td>0.3.0</td></tr><tr><td>Ignis</td><td>0.2.0</td></tr><tr><td>Aqua</td><td>0.5.3</td></tr><tr><td>IBM Q Provider</td><td>0.3.2rc1</td></tr><tr><th>System information</th></tr><tr><td>Python</td><td>3.7.4 (default, Aug 13 2019, 15:17:50) \n",
       "[Clang 4.0.1 (tags/RELEASE_401/final)]</td></tr><tr><td>OS</td><td>Darwin</td></tr><tr><td>CPUs</td><td>4</td></tr><tr><td>Memory (Gb)</td><td>16.0</td></tr><tr><td colspan='2'>Wed Aug 21 21:30:24 2019 EDT</td></tr></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style='width: 100%; background-color:#d5d9e0;padding-left: 10px; padding-bottom: 10px; padding-right: 10px; padding-top: 5px'><h3>This code is a part of Qiskit</h3><p>&copy; Copyright IBM 2017, 2019.</p><p>This code is licensed under the Apache License, Version 2.0. You may<br>obtain a copy of this license in the LICENSE.txt file in the root directory<br> of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.<p>Any modifications or derivative works of this code must retain this<br>copyright notice, and modified files need to carry a notice indicating<br>that they have been altered from the originals.</p></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import qiskit.tools.jupyter\n",
    "%qiskit_version_table\n",
    "%qiskit_copyright"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "celltoolbar": "Tags",
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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  "nteract": {
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  },
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    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
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